Whose Life Expectancy Views Drive Annuity Sales?
Researchers’ own “objective” life expectancy estimates have a bigger correlation with how likely U.S. consumers are to own annuities than the consumers’ own life expectancy estimates do, researchers say.
When Karolos Arapakis and Gal Wettstein calculated a consumer’s life expectancy themselves, one year of extra life expectancy correlated with an increase in the probability that a consumer would ever buy an annuity by 0.2 percentage points, to 9%, according to a new working paper.
When consumers estimated their own life expectancy, an extra year of consumer-predicted life expectancy correlated with an annuity ownership level increase of just 0.023 percentage points.
The researchers note that any correlation may not actually caused by consumers’ views about their life expectancy. Instead, the researchers say, the correlation could be a result of consumers’ views shaping both their ideas about life expectancy and their annuity purchases.
But, “taken at face value, the results are consistent with objective life expectancy having a much stronger effect on the decision of whether to buy an annuity than pessimism,” the researchers write.
What It Means
If the researchers are right, correcting insurers’ and clients’ ideas about how long the clients will live could have more of an effect on annuity ownership than making the clients more optimistic about their life expectancy.
Arapakis and Wettstein, economists at the Center for Retirement Research at Boston College, used data collected from 2000 through 2016 by the University of Michigan’s Health and Retirement Study survey program.
Survey program managers ask the participants about their health, their finances, and the likelihood that they will reach certain ages.
Arapakis and Wettstein used the data to calculate “subjective,” participant-provided life expectancies for each participant.
The economists also calculated their own “objective” life expectancies, based on the health and economic question answers, such as whether the participants had diabetes or other chronic health problems, then compared that objective, economist-calculated estimates with survey participants’ estimates.